Correlations and Scaling Laws in Human Mobility

TL;DR

This paper empirically investigates human mobility using GPS data, revealing scaling laws, correlations, and an abnormal transition in movement patterns, which contribute to understanding the underlying mechanisms of human movement behavior.

Contribution

It uncovers the relationship between displacement correlations and the power-law nature of individual movement distributions, highlighting factors behind scaling properties in human mobility.

Findings

Displacements show significant positive correlation at the population level.

Displacement distributions of strongly correlated individuals tend to follow power laws.

An abnormal transition in speed-displacement patterns was observed.

Abstract

Human mobility patterns deeply affect the dynamics of many social systems. In this paper, we empirically analyze the real-world human movements based GPS records, and observe rich scaling properties in the temporal-spatial patterns as well as an abnormal transition in the speed-displacement patterns. We notice that the displacements at the population level show significant positive correlation, indicating a cascade-like nature in human movements. Furthermore, our analysis at the individual level finds that the displacement distributions of users with strong correlation of displacements are closer to power laws, implying a relationship between the positive correlation of the series of displacements and the form of an individual's displacement distribution. These findings from our empirical analysis show a factor directly relevant to the origin of the scaling properties in human mobility.